This page contains the results of CoNGA analyses.
Results in tables may have been filtered to reduce redundancy,
focus on the most important columns, and
limit length; full tables should exist as OUTFILE_PREFIX*.tsv files.
Here we are assessing overall graph-vs-graph correlation by looking at
the shared edges between TCR and GEX neighbor graphs and comparing
that observed number to the number we would expect if the graphs were
completely uncorrelated. Our null model for uncorrelated graphs is to
take the vertices of one graph and randomly renumber them (permute their
labels). We compare the observed overlap to that expected under this null
model by computing a Z-score, either by permuting one of the graph's
vertices many times to get a mean and standard deviation of the overlap
distribution, or, for large graphs where this is time consuming,
by using a regression model for the
standard deviation. The different rows of this table correspond to the
different graph-graph comparisons that we make in the conga graph-vs-graph
analysis: we compare K-nearest-neighbor graphs for GEX and TCR at different
K values ("nbr_frac" aka neighbor-fraction, which reports K as a fraction
of the total number of clonotypes) to each other and to GEX and TCR "cluster"
graphs in which each clonotype is connected to all the other clonotypes with
the same (GEX or TCR) cluster assignment. For two K values (the default),
this gives 2*3=6 comparisons: GEX KNN graph vs TCR KNN graph, GEX cluster
graph vs TCR KNN graph, and GEX KNN graph vs TCR cluster graph, for each of the
two K values (aka nbr_fracs).
The column to look at is *overlap_zscore*. Higher values indicate more
significant GEX/TCR covariation, with "interesting" levels starting around
zscores of 3-5.
Columns in more detail:
graph_overlap_type: KNN ("nbr") or cluster versus KNN ("nbr") or cluster
nbr_frac: the K value for the KNN graph, as a fraction of total clonotypes
overlap: the observed overlap (number of shared edges) between GEX and TCR
graphs
expected_overlap: the expected overlap under a shuffled null model.
overlap_zscore: a Z-score for the observed overlap computed by subtracting
the expected overlap and dividing by the standard deviation estimated from
shuffling.
overlap
expected_overlap
overlap_mean
overlap_sdev
overlap_zscore
overlap_zscore_fitted
overlap_zscore_source
nodes
calculation_time
calculation_time_fitted
gex_edges
tcr_edges
gex_indegree_variance
gex_indegree_skewness
gex_indegree_kurtosis
tcr_indegree_variance
tcr_indegree_skewness
tcr_indegree_kurtosis
indegree_correlation_R
indegree_correlation_P
nbr_frac
graph_overlap_type
41
25.047081
25.71
6.255070
2.444417
4.397082
shuffling
532
0.059355
0.001543
2660
2660
1.414689
2.431343
9.051368
0.383277
0.932702
0.989053
0.066905
0.123253
0.01
gex_nbr_vs_tcr_nbr
289
261.920904
259.89
17.754940
1.639544
1.748683
shuffling
532
0.216329
0.017912
2660
27816
1.414689
2.431343
9.051368
0.194624
0.616989
-0.808238
0.029297
0.500129
0.01
gex_nbr_vs_tcr_cluster
470
402.749529
403.14
22.576988
2.961422
5.014587
shuffling
532
0.317310
0.028074
42772
2660
0.125965
-0.635407
-0.830691
0.383277
0.932702
0.989053
0.036501
0.400791
0.01
gex_cluster_vs_tcr_nbr
3043
2814.290019
2809.03
85.511924
2.736110
2.820836
shuffling
532
0.251573
0.174766
28196
28196
1.126519
1.580659
2.593195
0.258051
1.777979
6.075861
0.064742
0.135874
0.10
gex_nbr_vs_tcr_nbr
2846
2776.361582
2786.90
83.231545
0.710067
0.931263
shuffling
532
0.256546
0.172307
28196
27816
1.126519
1.580659
2.593195
0.194624
0.616989
-0.808238
0.036406
0.402021
0.10
gex_nbr_vs_tcr_cluster
4440
4269.145009
4268.83
77.180186
2.217797
2.752895
shuffling
532
0.446019
0.270063
42772
28196
0.125965
-0.635407
-0.830691
0.258051
1.777979
6.075861
-0.033397
0.442066
0.10
gex_cluster_vs_tcr_nbr
graph_vs_graph
Graph vs graph analysis looks for correlation between GEX and TCR space
by finding statistically significant overlap between two similarity graphs,
one defined by GEX similarity and one by TCR sequence similarity.
Overlap is defined one node (clonotype) at a time by looking for overlap
between that node's neighbors in the GEX graph and its neighbors in the
TCR graph. The null model is that the two neighbor sets are chosen
independently at random.
CoNGA looks at two kinds of graphs: K nearest neighbor (KNN) graphs, where
K = neighborhood size is specified as a fraction of the number of
clonotypes (defaults for K are 0.01 and 0.1), and cluster graphs, where
each clonotype is connected to all the other clonotypes in the same
(GEX or TCR) cluster. Overlaps are computed 3 ways (GEX KNN vs TCR KNN,
GEX KNN vs TCR cluster, and GEX cluster vs TCR KNN), for each of the
K values (called nbr_fracs short for neighbor fractions).
Columns (depend slightly on whether hit is KNN v KNN or KNN v cluster):
conga_score = P value for GEX/TCR overlap * number of clonotypes
mait_fraction = fraction of the overlap made up of 'invariant' T cells
num_neighbors* = size of neighborhood (K)
cluster_size = size of cluster (for KNN v cluster graph overlaps)
clone_index = 0-index of clonotype in adata object
conga_score
num_neighbors_gex
num_neighbors_tcr
overlap
overlap_corrected
mait_fraction
clone_index
nbr_frac
graph_overlap_type
cluster_size
gex_cluster
tcr_cluster
va
ja
cdr3a
vb
jb
cdr3b
0.120163
53.0
53.0
14
14
0.0
112
0.10
gex_nbr_vs_tcr_nbr
NaN
1
0
TRAV13-2*01
TRAJ45*01
CAETGGSANRLTF
TRBV27*01
TRBJ2-7*01
CASSFARTQYEQYF
0.134907
NaN
5.0
5
5
0.0
422
0.01
gex_cluster_vs_tcr_nbr
103.0
1
7
TRAV6*01
TRAJ37*01
CAPVSNTGKLIF
TRBV7-2*01
TRBJ1-4*01
CASSLPGGLGEKLFF
0.373793
5.0
5.0
2
2
0.0
34
0.01
gex_nbr_vs_tcr_nbr
NaN
7
0
TRAV12-1*01
TRAJ33*01
CAVRLDSNYQLIW
TRBV3-2*01
TRBJ2-1*01
CASRAAGGSNEQFF
0.373793
5.0
5.0
2
2
0.0
225
0.01
gex_nbr_vs_tcr_nbr
NaN
5
5
TRAV20*01
TRAJ11*01
CAVPRDGTLTF
TRBV5-7*01
TRBJ2-4*01
CASSFWTGEQNTQYF
0.378032
5.0
5.0
2
2
1.0
14
0.01
gex_nbr_vs_tcr_nbr
NaN
4
9
TRAV1-2*01
TRAJ33*01
CAVRDSNYQLIW
TRBV10-1*01
TRBJ2-6*01
CASSEEGGSGASVLTF
0.378032
5.0
5.0
2
2
1.0
16
0.01
gex_nbr_vs_tcr_nbr
NaN
4
9
TRAV1-2*01
TRAJ33*01
CAVRDSNYQLIW
TRBV4-3*01
TRBJ2-6*01
CASSQEGGGASVLTF
0.417430
NaN
53.0
14
14
0.0
35
0.10
gex_cluster_vs_tcr_nbr
59.0
4
10
TRAV12-1*01
TRAJ34*01
CAVRPRHNANKLIF
TRBV7-2*01
TRBJ2-2*01
CASSQQRLGGLANTAQLFF
0.556993
NaN
53.0
9
9
0.0
434
0.10
gex_cluster_vs_tcr_nbr
29.0
6
1
TRAV8-2*01
TRAJ27*01
CAVNDMRADKLTF
TRBV13*01
TRBJ2-5*01
CASSSSAEKGTQYF
0.696650
53.0
NaN
7
7
0.0
271
0.10
gex_nbr_vs_tcr_cluster
19.0
3
11
TRAV21*01
TRAJ47*01
CAVRPDYGNKLIF
TRBV13*01
TRBJ2-3*01
CASSPLPATDPQYF
0.696650
53.0
NaN
7
7
0.0
283
0.10
gex_nbr_vs_tcr_cluster
19.0
3
11
TRAV24*01
TRAJ9*01
CAFGTGGFKTVF
TRBV15*01
TRBJ1-5*01
CASSKQTGGSNQPQYF
0.726670
NaN
5.0
3
3
0.0
434
0.01
gex_cluster_vs_tcr_nbr
29.0
6
1
TRAV8-2*01
TRAJ27*01
CAVNDMRADKLTF
TRBV13*01
TRBJ2-5*01
CASSSSAEKGTQYF
0.802195
NaN
53.0
16
16
0.0
425
0.10
gex_cluster_vs_tcr_nbr
77.0
3
7
TRAV6*01
TRAJ41*01
CAAEDSGYALNF
TRBV5-8*01
TRBJ2-1*01
CASSWIGTGGSTEQFF
tcr_clumping
This table stores the results of the TCR "clumping"
analysis, which looks for neighborhoods in TCR space with more TCRs than
expected by chance under a simple null model of VDJ rearrangement.
For each TCR in the dataset, we count how many TCRs are within a set of
fixed TCRdist radii (defaults: 24,48,72,96), and compare that number
to the expected number given the size of the dataset using the poisson
model. Inspired by the ALICE and TCRnet methods.
Columns:
clump_type='global' unless we are optionally looking for TCR clumps within
the individual GEX clusters
num_nbrs = neighborhood size (number of other TCRs with TCRdist
clump_type
clone_index
nbr_radius
pvalue_adj
num_nbrs
expected_num_nbrs
raw_count
va
ja
cdr3a
vb
jb
cdr3b
clonotype_fdr_value
clumping_group
clusters_gex
clusters_tcr
global
87
48
0.000119
2
0.000334
1572.0
TRAV13-1*01
TRAJ36*01
CAAKDEVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASKDGYEQYF
0.000118
1
3
0
global
89
48
0.000328
2
0.000555
2615.0
TRAV13-1*01
TRAJ36*01
CAAKDGVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASTEAYEQYF
0.000118
1
2
0
global
88
48
0.000355
2
0.000578
2721.0
TRAV13-1*01
TRAJ36*01
CAAKDGVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASTLGYEQYF
0.000118
1
2
0
global
183
48
0.003560
2
0.001830
8617.0
TRAV19*01
TRAJ39*01
CALNERNNAGNVLTF
TRBV6-3*01
TRBJ2-3*01
CASSYSRGLSDPQYF
0.000890
2
2
2
global
239
96
0.011321
3
0.031976
150545.0
TRAV20*01
TRAJ43*01
CAHNDIRF
TRBV9*01
TRBJ2-1*01
CASSLWGELNEQFF
0.002127
3
2
5
global
515
24
0.013108
1
0.000006
29.0
TRAV9-2*01
TRAJ36*01
CALTQTGVNNLFF
TRBV20-1*01
TRBJ1-2*01
CSARDPRRTDYTF
0.002127
6
4
3
global
87
72
0.014886
2
0.003745
17632.0
TRAV13-1*01
TRAJ36*01
CAAKDEVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASKDGYEQYF
0.000118
1
3
0
global
89
72
0.025253
2
0.004880
22974.0
TRAV13-1*01
TRAJ36*01
CAAKDGVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASTEAYEQYF
0.000118
1
2
0
global
88
72
0.028254
2
0.005162
24303.0
TRAV13-1*01
TRAJ36*01
CAAKDGVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASTLGYEQYF
0.000118
1
2
0
global
514
24
0.036611
1
0.000017
81.0
TRAV9-2*01
TRAJ36*01
CALSQTGVNNLFF
TRBV20-1*01
TRBJ1-2*01
CSARDPRATDYTF
0.003661
6
4
3
global
331
96
0.043454
2
0.006404
30152.0
TRAV38-1*01
TRAJ27*01
CAFINTNADKLTF
TRBV13*01
TRBJ2-4*01
CASSLLVGGRENTQYF
0.003950
7
0
11
global
264
24
0.068249
1
0.000032
151.0
TRAV21*01
TRAJ31*01
CAVRNNNDRVIF
TRBV7-6*01
TRBJ1-1*01
CASSFSRNTEAFF
0.005250
4
1
10
global
263
24
0.068249
1
0.000032
151.0
TRAV21*01
TRAJ31*01
CAARNNNDRVIF
TRBV7-6*01
TRBJ1-1*01
CASSFSRNTEAFF
0.005250
4
2
10
global
403
72
0.086964
2
0.009068
42693.0
TRAV6*01
TRAJ23*01
CALAYNQAGKLIF
TRBV6-3*01
TRBJ2-5*01
CASSSLEETQYF
0.006212
5
2
7
global
89
24
0.112542
1
0.000053
249.0
TRAV13-1*01
TRAJ36*01
CAAKDGVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASTEAYEQYF
0.000118
1
2
0
global
88
24
0.120677
1
0.000057
267.0
TRAV13-1*01
TRAJ36*01
CAAKDGVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASTLGYEQYF
0.000118
1
2
0
global
240
96
0.147130
2
0.011806
55582.0
TRAV20*01
TRAJ43*01
CAVPVRF
TRBV9*01
TRBJ1-5*01
CASSPWGEDQPQYF
0.008260
3
3
5
global
183
96
0.148889
3
0.076316
359305.0
TRAV19*01
TRAJ39*01
CALNERNNAGNVLTF
TRBV6-3*01
TRBJ2-3*01
CASSYSRGLSDPQYF
0.000890
2
2
2
global
179
96
0.156943
2
0.012195
57413.0
TRAV19*01
TRAJ39*01
CALNERNNAGNVLTF
TRBV6-8*01
TRBJ2-1*01
CGSSYSRTGANNEQFF
0.008260
2
2
2
global
515
48
0.217395
1
0.000102
481.0
TRAV9-2*01
TRAJ36*01
CALTQTGVNNLFF
TRBV20-1*01
TRBJ1-2*01
CSARDPRRTDYTF
0.002127
6
4
3
global
242
96
0.224534
2
0.014598
68727.0
TRAV20*01
TRAJ43*01
CAVQDIRF
TRBV9*01
TRBJ1-1*01
CASSLWGENTEAFF
0.010692
3
2
5
global
183
72
0.235749
2
0.014960
70431.0
TRAV19*01
TRAJ39*01
CALNERNNAGNVLTF
TRBV6-3*01
TRBJ2-3*01
CASSYSRGLSDPQYF
0.000890
2
2
2
global
391
96
0.352987
2
0.018326
86279.0
TRAV5*01
TRAJ32*01
CAENYGGSGNKLIF
TRBV13*01
TRBJ2-3*01
CASSWLLGGTDPQYF
0.015347
8
3
11
global
183
24
0.397260
1
0.000187
879.0
TRAV19*01
TRAJ39*01
CALNERNNAGNVLTF
TRBV6-3*01
TRBJ2-3*01
CASSYSRGLSDPQYF
0.000890
2
2
2
global
242
48
0.418047
1
0.000196
925.0
TRAV20*01
TRAJ43*01
CAVQDIRF
TRBV9*01
TRBJ1-1*01
CASSLWGENTEAFF
0.010692
3
2
5
global
405
48
0.458266
1
0.000215
1014.0
TRAV6*01
TRAJ23*01
CALSYNQAGKLIF
TRBV6-3*01
TRBJ2-5*01
CASGNLQETQYF
0.017376
5
2
7
global
182
24
0.469145
1
0.000220
1042.0
TRAV19*01
TRAJ39*01
CALNERNNAGNVLTF
TRBV6-3*01
TRBJ2-3*01
CASSYSRGLTDPQYF
0.017376
2
2
2
global
514
48
0.504358
1
0.000237
1116.0
TRAV9-2*01
TRAJ36*01
CALSQTGVNNLFF
TRBV20-1*01
TRBJ1-2*01
CSARDPRATDYTF
0.003661
6
4
3
global
263
48
0.616873
1
0.000290
1365.0
TRAV21*01
TRAJ31*01
CAARNNNDRVIF
TRBV7-6*01
TRBJ1-1*01
CASSFSRNTEAFF
0.005250
4
2
10
global
264
48
0.616873
1
0.000290
1365.0
TRAV21*01
TRAJ31*01
CAVRNNNDRVIF
TRBV7-6*01
TRBJ1-1*01
CASSFSRNTEAFF
0.005250
4
1
10
global
87
96
0.653167
2
0.024984
117625.0
TRAV13-1*01
TRAJ36*01
CAAKDEVNNLFF
TRBV10-1*01
TRBJ2-7*01
CASKDGYEQYF
0.000118
1
3
0
global
405
96
0.793866
2
0.027567
129788.0
TRAV6*01
TRAJ23*01
CALSYNQAGKLIF
TRBV6-3*01
TRBJ2-5*01
CASGNLQETQYF
0.017376
5
2
7
tcr_clumping_logos
This figure summarizes the results of a CoNGA analysis that produces
scores (TCR clumping) and clusters. At the top are six
2D UMAP projections of clonotypes in the dataset based on GEX similarity
(top left three panels) and TCR similarity (top right three panels),
colored from left to right by GEX cluster assignment;
TCR clumping score; joint GEX:TCR cluster assignment for
clonotypes with significant TCR clumping scores,
using a bicolored disk whose left half indicates GEX cluster and whose right
half indicates TCR cluster; TCR cluster; TCR clumping; GEX:TCR cluster
assignments for TCR clumping hits, as in the third panel.
Below are two rows of GEX landscape plots colored by (first row, left)
expression of selected marker genes, (second row, left) Z-score normalized and
GEX-neighborhood averaged expression of the same marker genes, and
(both rows, right) TCR sequence features (see CoNGA manuscript Table S3 for
TCR feature descriptions).
GEX and TCR sequence features of TCR clumping hits in clusters with
3 or more hits are summarized by a series
of logo-style visualizations, from left to right:
differentially expressed genes (DEGs); TCR sequence logos showing the V and
J gene usage and CDR3 sequences for the TCR alpha and beta chains; biased
TCR sequence scores, with red indicating elevated scores and blue indicating
decreased scores relative to the rest of the dataset (see CoNGA manuscript
Table S3 for score definitions); GEX 'logos' for each cluster
consisting of a panel of marker genes shown with red disks colored by
mean expression and sized according to the fraction of cells expressing
the gene (gene names are given above).
DEG and TCRseq sequence logos are scaled
by the adjusted P value of the associations, with full logo height requiring
a top adjusted P value below 10-6. DEGs with fold-change less than 2 are shown
in gray. Each cluster is indicated by a bicolored disk colored according to
GEX cluster (left half) and TCR cluster (right half). The two numbers above
each disk show the number of hits within the cluster (on the left) and
the total number of cells in those clonotypes (on the right). The dendrogram
at the left shows similarity relationships among the clusters based on
connections in the GEX and TCR neighbor graphs.
The choice of which marker genes to use for the GEX umap panels and for the
cluster GEX logos can be configured using run_conga.py command line flags
or arguments to the conga.plotting.make_logo_plots function.
Image source: Rotelle_GIC_Final2_tcr_clumping_logos.png
tcr_db_match
This table stores significant matches between
TCRs in adata and TCRs in the file /scratch.global/ben_testing/conga/conga/data/new_paired_tcr_db_for_matching_nr.tsv
P values of matches are assigned by turning the raw TCRdist
score into a P value based on a model of the V(D)J rearrangement
process, so matches between TCRs that are very far from germline
(for example) are assigned a higher significance.
Columns:
tcrdist: TCRdist distance between the two TCRs (adata query and db hit)
pvalue_adj: raw P value of the match * num query TCRs * num db TCRs
fdr_value: Benjamini-Hochberg FDR value for match
clone_index: index within adata of the query TCR clonotype
db_index: index of the hit in the database being matched
va,ja,cdr3a,vb,jb,cdr3b
db_XXX: where XXX is a field in the literature database
tcr_graph_vs_gex_features
This table has results from a graph-vs-features analysis in which we
look for genes that are differentially expressed (elevated) in specific
neighborhoods of the TCR neighbor graph. Differential expression is
assessed by a ttest first, for speed, and then
by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value
passes an initial threshold (default is 10* the pvalue threshold).
Each row of the table represents a single significant association, in other
words a neighborhood (defined by the central clonotype index) and a
gene.
The columns are as follows:
ttest_pvalue_adj= ttest_pvalue * number of comparisons
mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons
log2enr = log2 fold change of gene in neighborhood (will be positive)
gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores
tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores
num_fg= the number of clonotypes in the neighborhood (including center)
mean_fg= the mean value of the feature in the neighborhood
mean_bg= the mean value of the feature outside the neighborhood
feature= the name of the gene
mait_fraction= the fraction of the skewed clonotypes that have an invariant
TCR
clone_index= the index in the anndata dataset of the clonotype that is the
center of the neighborhood.
ttest_pvalue_adj
mwu_pvalue_adj
log2enr
gex_cluster
tcr_cluster
feature
mean_fg
mean_bg
num_fg
clone_index
mait_fraction
nbr_frac
graph_type
feature_type
3.637877e-13
1.259886e-78
8.876144
3
7
ENSMMUG00000054409
2.968077
0.038523
33
-1
0.0
0.00
tcr_cluster
gex
4.330276e-20
2.475967e-37
6.343509
2
8
ENSMMUG00000061119
2.803675
0.174741
30
-1
0.0
0.00
tcr_cluster
gex
6.740658e-03
4.197116e-35
6.343996
2
7
ENSMMUG00000054409
1.696959
0.053418
54
399
0.0
0.10
tcr_nbr
gex
3.616694e-02
2.214514e-31
5.810826
2
7
ENSMMUG00000054409
1.581101
0.066507
54
404
0.0
0.10
tcr_nbr
gex
5.524648e-02
3.436715e-29
5.899136
3
7
ENSMMUG00000054409
1.601228
0.064233
54
402
0.0
0.10
tcr_nbr
gex
1.564020e-01
1.070536e-28
5.546289
2
7
ENSMMUG00000054409
1.518759
0.073550
54
419
0.0
0.10
tcr_nbr
gex
1.117727e-01
1.560612e-28
5.569513
2
7
ENSMMUG00000054409
1.524350
0.072918
54
421
0.0
0.10
tcr_nbr
gex
1.072842e-01
1.860159e-28
5.571641
2
7
ENSMMUG00000054409
1.524861
0.072860
54
422
0.0
0.10
tcr_nbr
gex
2.804220e-01
4.843464e-26
5.457238
2
7
ENSMMUG00000054409
1.497120
0.075994
54
417
0.0
0.10
tcr_nbr
gex
1.775188e-01
1.238556e-25
5.462943
2
7
ENSMMUG00000054409
1.498515
0.075837
54
407
0.0
0.10
tcr_nbr
gex
8.846428e-01
4.604450e-23
5.112633
2
7
ENSMMUG00000054409
1.410601
0.085768
54
408
0.0
0.10
tcr_nbr
gex
9.328553e-01
1.026424e-22
5.057032
3
7
ENSMMUG00000054409
1.396264
0.087388
54
418
0.0
0.10
tcr_nbr
gex
1.309988e+00
5.989549e-21
5.132640
2
7
ENSMMUG00000054409
1.415736
0.085188
54
406
0.0
0.10
tcr_nbr
gex
1.481972e+00
1.612634e-20
5.029298
3
7
ENSMMUG00000054409
1.389076
0.088200
54
423
0.0
0.10
tcr_nbr
gex
2.931209e-04
3.823810e-19
2.501481
0
2
ENSMMUG00000061119
0.951813
0.247530
57
-1
0.0
0.00
tcr_cluster
gex
3.435755e+00
2.149080e-18
4.922413
2
7
ENSMMUG00000054409
1.361163
0.091353
54
414
0.0
0.10
tcr_nbr
gex
3.285024e+00
2.149080e-18
4.917222
2
7
ENSMMUG00000054409
1.359799
0.091507
54
403
0.0
0.10
tcr_nbr
gex
3.335224e+00
2.288763e-18
4.909072
2
7
ENSMMUG00000054409
1.357656
0.091750
54
405
0.0
0.10
tcr_nbr
gex
3.389983e+00
3.069146e-18
4.880029
2
7
ENSMMUG00000054409
1.350005
0.092614
54
397
0.0
0.10
tcr_nbr
gex
3.860440e+00
4.199074e-18
4.827127
3
7
ENSMMUG00000054409
1.336010
0.094195
54
398
0.0
0.10
tcr_nbr
gex
3.572116e+00
4.859018e-18
4.833613
2
7
ENSMMUG00000054409
1.337729
0.094001
54
427
0.0
0.10
tcr_nbr
gex
3.933236e+00
5.621568e-18
4.796497
3
7
ENSMMUG00000054409
1.327874
0.095114
54
425
0.0
0.10
tcr_nbr
gex
5.550704e+00
1.755062e-17
4.551553
3
7
ENSMMUG00000054409
1.262026
0.102553
54
411
0.0
0.10
tcr_nbr
gex
2.649942e-09
8.465841e-17
4.280124
2
7
ENSMMUG00000056515
3.054797
0.713226
54
313
0.0
0.10
tcr_nbr
gex
1.089627e-08
8.958174e-17
4.308333
2
4
ENSMMUG00000056515
3.070184
0.711488
54
212
0.0
0.10
tcr_nbr
gex
3.592379e-02
2.390806e-16
2.487117
0
2
ENSMMUG00000061119
0.956520
0.251418
54
187
0.0
0.10
tcr_nbr
gex
7.090872e+00
2.836648e-16
4.820641
3
7
ENSMMUG00000054409
1.334289
0.094389
54
410
0.0
0.10
tcr_nbr
gex
1.893355e-09
3.523686e-16
4.323484
2
7
ENSMMUG00000056515
3.078450
0.710554
54
109
0.0
0.10
tcr_nbr
gex
8.125980e-02
5.935875e-16
2.423377
0
2
ENSMMUG00000061119
0.935882
0.253750
54
177
0.0
0.10
tcr_nbr
gex
1.043029e-01
1.005052e-15
2.668576
1
2
ENSMMUG00000061119
1.016149
0.244682
54
200
0.0
0.10
tcr_nbr
gex
8.291229e-08
6.401231e-15
4.098499
2
7
ENSMMUG00000056515
2.955863
0.724403
54
412
0.0
0.10
tcr_nbr
gex
5.006807e-08
1.275900e-14
4.169137
2
7
ENSMMUG00000056515
2.994312
0.720059
54
277
0.0
0.10
tcr_nbr
gex
1.643447e-07
1.420431e-14
4.115502
2
4
ENSMMUG00000056515
2.965114
0.723357
54
222
0.0
0.10
tcr_nbr
gex
5.138232e-01
4.277048e-14
2.573013
0
2
ENSMMUG00000061119
0.984590
0.248247
54
162
0.0
0.10
tcr_nbr
gex
1.149504e+00
1.472213e-13
2.417194
0
2
ENSMMUG00000061119
0.933889
0.253975
54
179
0.0
0.10
tcr_nbr
gex
5.304837e-01
1.675102e-13
2.355310
0
2
ENSMMUG00000061119
0.914030
0.256218
54
160
0.0
0.10
tcr_nbr
gex
4.001114e-07
2.380009e-13
4.056406
2
4
ENSMMUG00000056515
2.932970
0.726989
54
55
0.0
0.10
tcr_nbr
gex
7.951065e-01
4.733059e-13
2.244093
0
2
ENSMMUG00000061119
0.878763
0.260203
54
196
0.0
0.10
tcr_nbr
gex
4.891390e-05
1.930714e-12
3.767220
2
4
ENSMMUG00000056515
2.776131
0.744707
54
320
0.0
0.10
tcr_nbr
gex
7.886987e+00
2.056620e-12
7.482114
3
7
ENSMMUG00000054409
3.600625
0.181684
6
399
0.0
0.01
tcr_nbr
gex
8.158782e+00
2.166197e-12
7.472014
3
7
ENSMMUG00000054409
3.594243
0.181757
6
397
0.0
0.01
tcr_nbr
gex
6.733624e+00
2.665200e-12
7.419899
3
7
ENSMMUG00000054409
3.561323
0.182133
6
412
0.0
0.01
tcr_nbr
gex
4.574165e+00
2.955696e-12
7.486300
3
7
ENSMMUG00000054409
3.603271
0.181654
6
402
0.0
0.01
tcr_nbr
gex
9.128151e+00
3.277424e-12
7.391793
3
7
ENSMMUG00000054409
3.543579
0.182335
6
415
0.0
0.01
tcr_nbr
gex
1.203081e+00
3.527318e-12
2.308465
1
2
ENSMMUG00000061119
0.899108
0.257904
54
184
0.0
0.10
tcr_nbr
gex
2.526534e+00
3.848063e-12
2.324406
0
2
ENSMMUG00000061119
0.904175
0.257332
54
193
0.0
0.10
tcr_nbr
gex
4.742955e-06
4.282523e-12
3.853640
0
7
ENSMMUG00000056515
2.822914
0.739422
54
413
0.0
0.10
tcr_nbr
gex
5.670211e-05
6.391235e-12
3.708465
2
7
ENSMMUG00000056515
2.744373
0.748295
54
126
0.0
0.10
tcr_nbr
gex
2.339934e-05
6.922410e-12
3.757844
2
7
ENSMMUG00000056515
2.771061
0.745280
54
28
0.0
0.10
tcr_nbr
gex
1.752553e-05
8.879416e-12
3.852103
2
4
ENSMMUG00000056515
2.822081
0.739516
54
415
0.0
0.10
tcr_nbr
gex
Omitted 82 lines
tcr_graph_vs_gex_features_plot
This plot summarizes the results of a graph
versus features analysis by labeling the clonotypes at the center of
each biased neighborhood with the name of the feature biased in that
neighborhood. The feature names are drawn in colored boxes whose
color is determined by the strength and direction of the feature score bias
(from bright red for features that are strongly elevated to bright blue
for features that are strongly decreased in the corresponding neighborhoods,
relative to the rest of the dataset).
At most one feature (the top scoring) is shown for each clonotype
(ie, neighborhood). The UMAP xy coordinates for this plot are
stored in adata.obsm['X_tcr_2d']. The score used for ranking correlations
is 'mwu_pvalue_adj'. The threshold score for displaying a feature is
1.0. The feature column is 'feature'. Since
we also run graph-vs-features using "neighbor" graphs that are defined
by clusters, ie where each clonotype is connected to all the other
clonotypes in the same cluster, some biased features may be associated with
a cluster rather than a specific clonotype. Those features are labeled with
a '*' at the end and shown near the centroid of the clonotypes belonging
to that cluster.
Image source: Rotelle_GIC_Final2_tcr_graph_vs_gex_features_plot.png
tcr_graph_vs_gex_features_panels
Graph-versus-feature analysis was used to identify
a set of GEX features that showed biased distributions
in TCR neighborhoods. This plot shows the distribution of the
top-scoring GEX features on the TCR
UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie
Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons).
At most 3 features from clonotype neighbhorhoods
in each (GEX,TCR) cluster pair are shown. The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Points are plotted in order of increasing feature score.
Image source: Rotelle_GIC_Final2_tcr_graph_vs_gex_features_panels.png
tcr_genes_vs_gex_features
This table has results from a graph-vs-features analysis in which we
look for genes that are differentially expressed (elevated) in specific
neighborhoods of the TCR neighbor graph. Differential expression is
assessed by a ttest first, for speed, and then
by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value
passes an initial threshold (default is 10* the pvalue threshold).
Each row of the table represents a single significant association, in other
words a neighborhood (defined by the central clonotype index) and a
gene.
The columns are as follows:
ttest_pvalue_adj= ttest_pvalue * number of comparisons
mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons
log2enr = log2 fold change of gene in neighborhood (will be positive)
gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores
tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores
num_fg= the number of clonotypes in the neighborhood (including center)
mean_fg= the mean value of the feature in the neighborhood
mean_bg= the mean value of the feature outside the neighborhood
feature= the name of the gene
mait_fraction= the fraction of the skewed clonotypes that have an invariant
TCR
clone_index= the index in the anndata dataset of the clonotype that is the
center of the neighborhood.
In this analysis the TCR graph is defined by
connecting all clonotypes that have the same VA/JA/VB/JB-gene segment
(it's run four times, once with each gene segment type)
ttest_pvalue_adj
mwu_pvalue_adj
log2enr
gex_cluster
tcr_cluster
feature
mean_fg
mean_bg
num_fg
clone_index
mait_fraction
gene_segment
graph_type
feature_type
7.484724e-15
8.969480e-92
11.094260
3
5
ENSMMUG00000049767
3.527550
0.015000
18
-1
0.0
TRBV5-8
tcr_genes
gex
1.055481e-18
5.106906e-84
9.171846
2
7
ENSMMUG00000054409
3.159566
0.038370
31
-1
0.0
TRAV6
tcr_genes
gex
8.999149e-17
1.240647e-79
10.937514
0
1
ENSMMUG00000063185
3.774666
0.021480
24
-1
0.0
TRBV4-2
tcr_genes
gex
4.632209e-13
1.034259e-64
9.338192
7
3
ENSMMUG00000062211
4.019811
0.081115
21
-1
0.0
TRBV12-2
tcr_genes
gex
2.928629e-01
2.430952e-63
8.472871
6
1
ENSMMUG00000056910
2.271786
0.024183
11
-1
0.0
TRAV16
tcr_genes
gex
6.316045e-13
2.839198e-51
8.579260
6
1
ENSMMUG00000060662
3.342130
0.068893
15
-1
0.0
TRAV8-7
tcr_genes
gex
1.107452e-12
9.851018e-46
8.352445
0
4
ENSMMUG00000062085
3.413647
0.086066
21
-1
0.2
TRBV4-3
tcr_genes
gex
1.855973e-02
1.242521e-39
9.308708
2
4
ENSMMUG00000059325
2.991692
0.029397
8
-1
0.0
TRAV25
tcr_genes
gex
8.302680e-06
1.467056e-37
6.595270
0
1
ENSMMUG00000057062
1.951733
0.060604
15
-1
0.0
TRAV8-3
tcr_genes
gex
1.226911e-19
7.015239e-37
6.343509
2
8
ENSMMUG00000061119
2.803675
0.174741
30
-1
0.0
TRAV18
tcr_genes
gex
2.178532e-106
1.600235e-36
5.592459
2
7
ENSMMUG00000056515
3.728990
0.610970
58
-1
0.0
TRBV6-3
tcr_genes
gex
1.344410e-10
1.066049e-35
7.692902
7
0
ENSMMUG00000043894
3.622388
0.162158
19
-1
0.0
TRBV20-1
tcr_genes
gex
3.968732e-01
3.184652e-34
5.313467
6
1
ENSMMUG00000061081
1.256408
0.061273
19
-1
0.0
TRAV8-2
tcr_genes
gex
6.087152e+00
5.246990e-34
8.162003
0
3
ENSMMUG00000061255
2.457652
0.036600
7
-1
0.0
TRBV5-6
tcr_genes
gex
3.710291e-10
5.752428e-29
7.097247
2
2
ENSMMUG00000051385
3.573801
0.225597
23
-1
0.0
TRBV7-6
tcr_genes
gex
9.155726e-05
2.140831e-26
7.509862
6
0
ENSMMUG00000062974
2.936639
0.093444
12
-1
0.0
TRAV13-2
tcr_genes
gex
7.397531e-03
3.309419e-23
7.249660
2
8
ENSMMUG00000062211
3.442710
0.181418
9
-1
0.0
TRBV12-3
tcr_genes
gex
3.152396e-05
3.535373e-22
2.727790
0
2
ENSMMUG00000061119
1.043334
0.244951
52
-1
0.0
TRAV19
tcr_genes
gex
1.739503e-02
1.019891e-21
7.777559
2
4
ENSMMUG00000065017
3.209041
0.102794
9
-1
0.0
TRAV12-1
tcr_genes
gex
1.221002e-34
8.738056e-17
5.363096
2
4
ENSMMUG00000056515
3.915709
0.786193
28
-1
0.0
TRBV6-2
tcr_genes
gex
2.784245e-02
6.241326e-12
6.818597
2
1
ENSMMUG00000043894
3.442513
0.237543
8
-1
0.0
TRBV21-1
tcr_genes
gex
7.080497e-03
9.877314e-07
6.670205
2
10
ENSMMUG00000051385
3.695223
0.326019
7
-1
0.0
TRBV7-4
tcr_genes
gex
1.119380e-01
7.839223e-05
4.851182
4
10
ENSMMUG00000051385
2.545002
0.341355
7
-1
0.0
TRBV5-6
tcr_genes
gex
3.726081e-06
7.382818e-04
4.167548
2
1
ENSMMUG00000056515
3.269982
0.878995
16
-1
0.0
TRBV10-2
tcr_genes
gex
1.901853e-08
1.002423e-03
2.294030
4
5
ENSMMUG00000056515
2.074884
0.883734
30
-1
0.0
TRBV9
tcr_genes
gex
5.107602e+00
1.005481e-03
6.362424
0
5
ENSMMUG00000043894
3.249662
0.263284
4
-1
0.0
TRBV19
tcr_genes
gex
8.124517e-01
4.614008e-02
1.227987
5
4
WASHC3
0.765917
0.399690
64
-1
0.0
TRBJ2-4
tcr_genes
gex
4.676707e+00
7.089933e-02
2.693193
7
9
MAP2K3
1.100824
0.270232
9
-1
0.0
TRBV6-1
tcr_genes
gex
3.887516e-77
4.397661e-01
7.171084
3
2
ENSMMUG00000051385
4.114374
0.349118
3
-1
0.0
TRBV7-7
tcr_genes
gex
4.484605e-01
2.270749e+00
0.888811
0
0
SLA
1.824650
1.337273
56
-1
0.0
TRBJ2-3
tcr_genes
gex
7.139158e-01
3.073687e+00
3.521512
7
1
TMEM135
0.964564
0.132244
3
-1
0.0
TRAV8-4
tcr_genes
gex
8.406671e-01
8.569616e+00
3.399464
7
1
CSTF3
0.964564
0.143120
3
-1
0.0
TRAV8-4
tcr_genes
gex
tcr_genes_vs_gex_features_panels
Graph-versus-feature analysis was used to identify
a set of GEX features that showed biased distributions
in TCR neighborhoods. This plot shows the distribution of the
top-scoring GEX features on the TCR
UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie
Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons).
At most 3 features from clonotype neighbhorhoods
in each (GEX,TCR) cluster pair are shown. The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Points are plotted in order of increasing feature score.
Image source: Rotelle_GIC_Final2_tcr_genes_vs_gex_features_panels.png
gex_graph_vs_tcr_features
This table has results from a graph-vs-features analysis in which we
look at the distribution of a set of TCR-defined features over the GEX
neighbor graph. We look for neighborhoods in the graph that have biased
score distributions, as assessed by a ttest first, for speed, and then
by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value
passes an initial threshold (default is 10* the pvalue threshold).
Each row of the table represents a single significant association, in other
words a neighborhood (defined by the central clonotype index) and a
tcr feature.
The columns are as follows:
ttest_pvalue_adj= ttest_pvalue * number of comparisons
ttest_stat= ttest statistic (sign indicates where feature is up or down)
mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons
gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores
tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores
num_fg= the number of clonotypes in the neighborhood (including center)
mean_fg= the mean value of the feature in the neighborhood
mean_bg= the mean value of the feature outside the neighborhood
feature= the name of the TCR score
mait_fraction= the fraction of the skewed clonotypes that have an invariant
TCR
clone_index= the index in the anndata dataset of the clonotype that is the
center of the neighborhood.
ttest_pvalue_adj
ttest_stat
mwu_pvalue_adj
gex_cluster
tcr_cluster
num_fg
mean_fg
mean_bg
feature
mait_fraction
clone_index
nbr_frac
graph_type
feature_type
3.636894e-27
2.435638e+06
1.562678e-112
4
9
6
1.000000
0.000000
mait
1.000000
12
0.01
gex_nbr
tcr
0.000000e+00
1.845495e+02
9.519093e-46
4
9
6
1.000000
0.015209
TRAV1-2
1.000000
12
0.01
gex_nbr
tcr
3.867305e-01
-4.951298e+00
2.348437e-01
2
0
54
0.506821
0.795354
af4
0.000000
26
0.10
gex_nbr
tcr
9.933085e-02
-4.471693e+00
4.333296e-01
7
0
29
-0.126722
0.222531
cd8
0.000000
-1
0.00
gex_cluster
tcr
2.098956e-01
-5.082872e+00
7.249505e-01
2
0
54
0.523511
0.793468
af4
0.153846
12
0.10
gex_nbr
tcr
1.007617e+00
3.463887e+00
9.733440e-01
4
9
60
-5.399413
-5.587273
mjenergy
0.266667
-1
0.00
gex_cluster
tcr
4.460173e-01
3.724043e+00
9.859175e-01
4
5
60
0.720707
0.700891
nndists_tcr
0.066667
-1
0.00
gex_cluster
tcr
4.178701e-02
-4.250926e+00
3.201596e+00
3
6
78
0.064103
0.207048
TRBJ2-1
0.000000
-1
0.00
gex_cluster
tcr
1.389785e-11
-7.971102e+00
5.620059e+00
4
6
60
0.000000
0.118644
TRBJ2-3
0.000000
-1
0.00
gex_cluster
tcr
gex_graph_vs_tcr_features_plot
This plot summarizes the results of a graph
versus features analysis by labeling the clonotypes at the center of
each biased neighborhood with the name of the feature biased in that
neighborhood. The feature names are drawn in colored boxes whose
color is determined by the strength and direction of the feature score bias
(from bright red for features that are strongly elevated to bright blue
for features that are strongly decreased in the corresponding neighborhoods,
relative to the rest of the dataset).
At most one feature (the top scoring) is shown for each clonotype
(ie, neighborhood). The UMAP xy coordinates for this plot are
stored in adata.obsm['X_gex_2d']. The score used for ranking correlations
is 'mwu_pvalue_adj'. The threshold score for displaying a feature is
1.0. The feature column is 'feature'. Since
we also run graph-vs-features using "neighbor" graphs that are defined
by clusters, ie where each clonotype is connected to all the other
clonotypes in the same cluster, some biased features may be associated with
a cluster rather than a specific clonotype. Those features are labeled with
a '*' at the end and shown near the centroid of the clonotypes belonging
to that cluster.
Image source: Rotelle_GIC_Final2_gex_graph_vs_tcr_features_plot.png
gex_graph_vs_tcr_features_panels
Graph-versus-feature analysis was used to identify
a set of TCR features that showed biased distributions
in GEX neighborhoods. This plot shows the distribution of the
top-scoring TCR features on the GEX
UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie
Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons).
At most 3 features from clonotype neighbhorhoods
in each (GEX,TCR) cluster pair are shown. The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Points are plotted in order of increasing feature score.
Image source: Rotelle_GIC_Final2_gex_graph_vs_tcr_features_panels.png
graph_vs_features_gex_clustermap
This plot shows the distribution of significant
features from graph-vs-features or HotSpot analysis plotted across the
GEX landscape. Rows are features and columns are
individual clonotypes. Columns are ordered by hierarchical clustering
(if a dendrogram is present above the heatmap) or by a 1D UMAP projection
(used for very large datasets or if 'X_pca_gex' is not present in
adata.obsm_keys()). Rows are ordered by hierarchical clustering with
a correlation metric.
The row colors to the left of the heatmap show the feature type
(blue=TCR, orange=GEX). The row colors to the left of those
indicate the strength of the graph-vs-feature correlation
(also included in the feature labels to the right of the heatmap;
keep in mind that highly significant P values for some features may shift
the colorscale so everything else looks dark blue).
The column colors above the heatmap are GEX clusters
(and TCR V/J genes if plotting against the TCR landscape). The text
above the column colors provides more info.
Feature scores are Z-score normalized and then averaged over the
K=53 nearest neighbors (0 means no nbr-averaging).
The 'coolwarm' colormap is centered at Z=0.
Since features of the same type (GEX or TCR) as the landscape and
neighbor graph (ie GEX features) are more highly
correlated over graph neighborhoods, their neighbor-averaged scores
will show more extreme variation. For this reason, the nbr-averaged
scores for these features from the same modality as the landscape
itself are downscaled by a factor of
rescale_factor_for_self_features=0.33.
The colormap in the top left is for the Z-score normalized,
neighbor-averaged scores (multiply by 3.03
to get the color scores for the GEX features).
This plot shows the distribution of significant
features from graph-vs-features or HotSpot analysis plotted across the
TCR landscape. Rows are features and columns are
individual clonotypes. Columns are ordered by hierarchical clustering
(if a dendrogram is present above the heatmap) or by a 1D UMAP projection
(used for very large datasets or if 'X_pca_tcr' is not present in
adata.obsm_keys()). Rows are ordered by hierarchical clustering with
a correlation metric.
The row colors to the left of the heatmap show the feature type
(blue=TCR, orange=GEX). The row colors to the left of those
indicate the strength of the graph-vs-feature correlation
(also included in the feature labels to the right of the heatmap;
keep in mind that highly significant P values for some features may shift
the colorscale so everything else looks dark blue).
The column colors above the heatmap are TCR clusters
(and TCR V/J genes if plotting against the TCR landscape). The text
above the column colors provides more info.
Feature scores are Z-score normalized and then averaged over the
K=53 nearest neighbors (0 means no nbr-averaging).
The 'coolwarm' colormap is centered at Z=0.
Since features of the same type (GEX or TCR) as the landscape and
neighbor graph (ie TCR features) are more highly
correlated over graph neighborhoods, their neighbor-averaged scores
will show more extreme variation. For this reason, the nbr-averaged
scores for these features from the same modality as the landscape
itself are downscaled by a factor of
rescale_factor_for_self_features=0.33.
The colormap in the top left is for the Z-score normalized,
neighbor-averaged scores (multiply by 3.03
to get the color scores for the TCR features).
Summary figure for the graph-vs-graph and
graph-vs-features analyses.
Image source: Rotelle_GIC_Final2_graph_vs_summary.png
gex_clusters_tcrdist_trees
These are TCRdist hierarchical clustering trees
for the GEX clusters (cluster assignments stored in
adata.obs['clusters_gex']). The trees are colored by CoNGA score
with a color score range of 5.32e+00 (blue) to 5.32e-09 (red).
For coloring, CoNGA scores are log-transformed, negated, and square-rooted
(with an offset in there, too, roughly speaking).
Image source: Rotelle_GIC_Final2_gex_clusters_tcrdist_trees.png
conga_threshold_tcrdist_tree
This is a TCRdist hierarchical clustering tree
for the clonotypes with CoNGA score less than 10.0.
The tree is colored by CoNGA score
with a color score range of 1.00e+01 (blue) to 1.00e-08 (red).
For coloring, CoNGA scores are log-transformed, negated, and square-rooted
(with an offset in there, too, roughly speaking).
Image source: Rotelle_GIC_Final2_conga_threshold_tcrdist_tree.png
hotspot_features
Find GEX (TCR) features that show a biased
distribution across the TCR (GEX) neighbor graph,
using a simplified version of the Hotspot method
from the Yosef lab.
DeTomaso, D., & Yosef, N. (2021).
"Hotspot identifies informative gene modules across modalities
of single-cell genomics."
Cell Systems, 12(5), 446–456.e9.
PMID:33951459
Columns:
Z: HotSpot Z statistic
pvalue_adj: Raw P value times the number of tests (crude Bonferroni
correction)
nbr_frac: The K NN nbr fraction used for the neighbor graph construction
(nbr_frac = 0.1 means K=0.1*num_clonotypes neighbors)
Z
pvalue_adj
feature
feature_type
nbr_frac
49.336595
0.000000e+00
ENSMMUG00000056515
gex
0.10
40.232142
0.000000e+00
ENSMMUG00000054409
gex
0.10
37.780389
0.000000e+00
ENSMMUG00000061119
gex
0.10
30.231293
6.114312e-197
ENSMMUG00000054409
gex
0.01
23.005884
2.707485e-113
ENSMMUG00000061119
gex
0.01
20.949730
1.255227e-93
ENSMMUG00000056515
gex
0.01
19.998144
3.802338e-85
ENSMMUG00000062211
gex
0.10
19.768175
4.393179e-85
mait
tcr
0.01
18.625673
1.323592e-73
ENSMMUG00000063185
gex
0.10
16.644333
2.212818e-58
ENSMMUG00000051385
gex
0.10
16.490307
2.865384e-57
ENSMMUG00000049767
gex
0.10
16.440923
6.480665e-57
ENSMMUG00000043894
gex
0.10
15.019460
3.642073e-47
RORC
gex
0.01
14.974161
7.205824e-47
ENSMMUG00000062085
gex
0.10
13.580694
3.467705e-38
ENSMMUG00000063185
gex
0.01
12.154972
3.590778e-30
ENSMMUG00000062211
gex
0.01
12.041434
1.431390e-29
ENSMMUG00000043894
gex
0.01
11.386613
3.243373e-26
ENSMMUG00000057062
gex
0.10
11.078364
1.062752e-24
ENSMMUG00000059325
gex
0.10
11.061355
1.284877e-24
ENSMMUG00000060662
gex
0.10
10.571318
2.692498e-22
BLK
gex
0.01
10.533641
4.021138e-22
ENSMMUG00000057062
gex
0.01
10.423756
1.284975e-21
ENSMMUG00000051385
gex
0.01
9.397822
3.705435e-17
ENSMMUG00000059234
gex
0.01
8.959303
2.173455e-15
ENSMMUG00000062085
gex
0.01
8.951750
2.327481e-15
ENSMMUG00000060662
gex
0.01
8.771732
1.170346e-14
KLRB1
gex
0.01
8.690750
2.395083e-14
ENSMMUG00000065017
gex
0.01
8.649237
3.448732e-14
ENSMMUG00000061255
gex
0.10
8.565631
7.149958e-14
TYROBP
gex
0.01
8.352788
4.434904e-13
ENSMMUG00000049767
gex
0.01
7.703842
1.036472e-12
TRAV1-2
tcr
0.01
7.995739
8.567680e-12
ENSMMUG00000061255
gex
0.01
7.391101
9.686542e-10
ENSMMUG00000061081
gex
0.10
7.316706
1.690483e-09
ENSMMUG00000052673
gex
0.10
7.273446
2.331063e-09
ENSMMUG00000056431
gex
0.10
7.221398
3.422829e-09
ENSMMUG00000061499
gex
0.01
7.077887
9.736488e-09
STAP1
gex
0.01
6.457199
7.094916e-07
ENSMMUG00000016687
gex
0.01
5.719503
8.386610e-07
mait
tcr
0.10
6.393141
1.081032e-06
KNTC1
gex
0.01
6.348860
1.442928e-06
ENSMMUG00000065017
gex
0.10
5.406902
5.033755e-06
TRAV12-1
tcr
0.01
6.007525
1.253080e-05
ENSMMUG00000062974
gex
0.10
5.910594
2.267504e-05
ENSMMUG00000059325
gex
0.01
5.892373
2.532342e-05
C1H1orf53
gex
0.01
5.764445
5.449768e-05
ENSMMUG00000049338
gex
0.01
5.762043
5.527917e-05
ENSMMUG00000056431
gex
0.01
5.467192
3.041440e-04
ADA2
gex
0.01
5.392620
4.618999e-04
ENSMMUG00000056910
gex
0.10
Omitted 15 lines
hotspot_gex_umap
HotSpot analysis (Nir Yosef lab, PMID: 33951459)
was used to identify a set of GEX (TCR) features that showed biased
distributions in TCR (GEX) space. This plot shows the distribution of the
top-scoring HotSpot features on the GEX
UMAP 2D landscape. The features are ranked by adjusted P value
(raw P value * number of comparisons). The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Features are filtered based on correlation coefficient to reduce
redundancy: if a feature has a correlation of >= 0.9
(the max_feature_correlation argument to conga.plotting.plot_hotspot_umap)
to a previously plotted feature, that feature is skipped.
Points are plotted in order of increasing feature score
Image source: Rotelle_GIC_Final2_hotspot_combo_features_0.100_nbrs_gex_plot_umap_nbr_avg.png
hotspot_gex_clustermap
This plot shows the distribution of significant
features from graph-vs-features or HotSpot analysis plotted across the
GEX landscape. Rows are features and columns are
individual clonotypes. Columns are ordered by hierarchical clustering
(if a dendrogram is present above the heatmap) or by a 1D UMAP projection
(used for very large datasets or if 'X_pca_gex' is not present in
adata.obsm_keys()). Rows are ordered by hierarchical clustering with
a correlation metric.
The row colors to the left of the heatmap show the feature type
(blue=TCR, orange=GEX). The row colors to the left of those
indicate the strength of the graph-vs-feature correlation
(also included in the feature labels to the right of the heatmap;
keep in mind that highly significant P values for some features may shift
the colorscale so everything else looks dark blue).
The column colors above the heatmap are GEX clusters
(and TCR V/J genes if plotting against the TCR landscape). The text
above the column colors provides more info.
Feature scores are Z-score normalized and then averaged over the
K=53 nearest neighbors (0 means no nbr-averaging).
The 'coolwarm' colormap is centered at Z=0.
Since features of the same type (GEX or TCR) as the landscape and
neighbor graph (ie GEX features) are more highly
correlated over graph neighborhoods, their neighbor-averaged scores
will show more extreme variation. For this reason, the nbr-averaged
scores for these features from the same modality as the landscape
itself are downscaled by a factor of
rescale_factor_for_self_features=0.33.
The colormap in the top left is for the Z-score normalized,
neighbor-averaged scores (multiply by 3.03
to get the color scores for the GEX features).
HotSpot analysis (Nir Yosef lab, PMID: 33951459)
was used to identify a set of GEX (TCR) features that showed biased
distributions in TCR (GEX) space. This plot shows the distribution of the
top-scoring HotSpot features on the TCR
UMAP 2D landscape. The features are ranked by adjusted P value
(raw P value * number of comparisons). The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Features are filtered based on correlation coefficient to reduce
redundancy: if a feature has a correlation of >= 0.9
(the max_feature_correlation argument to conga.plotting.plot_hotspot_umap)
to a previously plotted feature, that feature is skipped.
Points are plotted in order of increasing feature score
Image source: Rotelle_GIC_Final2_hotspot_combo_features_0.100_nbrs_tcr_plot_umap_nbr_avg.png
hotspot_tcr_clustermap
This plot shows the distribution of significant
features from graph-vs-features or HotSpot analysis plotted across the
TCR landscape. Rows are features and columns are
individual clonotypes. Columns are ordered by hierarchical clustering
(if a dendrogram is present above the heatmap) or by a 1D UMAP projection
(used for very large datasets or if 'X_pca_tcr' is not present in
adata.obsm_keys()). Rows are ordered by hierarchical clustering with
a correlation metric.
The row colors to the left of the heatmap show the feature type
(blue=TCR, orange=GEX). The row colors to the left of those
indicate the strength of the graph-vs-feature correlation
(also included in the feature labels to the right of the heatmap;
keep in mind that highly significant P values for some features may shift
the colorscale so everything else looks dark blue).
The column colors above the heatmap are TCR clusters
(and TCR V/J genes if plotting against the TCR landscape). The text
above the column colors provides more info.
Feature scores are Z-score normalized and then averaged over the
K=53 nearest neighbors (0 means no nbr-averaging).
The 'coolwarm' colormap is centered at Z=0.
Since features of the same type (GEX or TCR) as the landscape and
neighbor graph (ie TCR features) are more highly
correlated over graph neighborhoods, their neighbor-averaged scores
will show more extreme variation. For this reason, the nbr-averaged
scores for these features from the same modality as the landscape
itself are downscaled by a factor of
rescale_factor_for_self_features=0.33.
The colormap in the top left is for the Z-score normalized,
neighbor-averaged scores (multiply by 3.03
to get the color scores for the TCR features).